Principle

The SoDa TMY methodology is based on the following:

For the "median" TMY (P50), we are computing a FS50 TMY with the minimum Finkelstein-Schafer distance for each month versus the average monthly cumulated distribution of the month. The difference with the standard Sandia approach (linear weighted combination of different variables) is to use a "driver" representative of the solar technology of interest for the project, for instance:

For a fixed tilted PV system, we will use simply the hourly Global Tilted Irradiation

For a 1 axis PV system, we will use the hourly computed in plane irradiation (with tilt angle limit and a simple standard backtracking scheme)

For a CPV system, we will use the DNI, excluding the hours when the wind exceeds a maximum speed (depends from the tracking system limits)

For a CSP system, we will use the DNI corrected with the cosine of incidence angle effect and the limits of the range for tilt

Any other parameter could be taken into account, like temperature, if its incidence on the system yield can be expressed with an equation

Please find in the attachment a summary of some work comparing this approach and the Sandia approach for a CPV project study. (Slides_TMY_Transvalor_Driver_approach.pdf dans /soda-products de mon ordi => ôter le nom des clients)

This approach is the result of a work package in the European Research Project ENDORSE. Some further explanations on the TMY can be found in the corresponding web page of the project here:

The P90 TMY is computed with the percentile method, also for the "driver" value. With the 12 full years of data available from HelioClim3-v5, the standard deviation of the long term annual values of the driver irradiation is computed and multiplied by 1.28155 to obtain a P90 estimate. Then, the P90 representative year is chosen as the year for which the annual sum of the driver irradiation is the closest to the P90 estimation. As the number of years is not large, the P90 year is nearly at all times either the worst year or the second worst year in the long term time series. Numerous other variants exist to compute a P90, but it is very difficult to determine which one is the best due to the relatively short number of years available for a given site compared to what would be really necessary to do a statistical P90 approach.

In our "Long term time series analysis report", which is a standard companion report to our TMY analysis, we do an annual P90 statistical approach, including also the P90 evolution when looking at the expectations for multiple consecutive years.